Bright Data と Google Gemini を使用した LinkedIn から企業ストーリーの生成
上級
これはSales, AI, Marketing分野の自動化ワークフローで、19個のノードを含みます。主にIf, Set, Wait, HttpRequest, ManualTriggerなどのノードを使用、AI技術を活用したスマート自動化を実現。 Bright DataとGoogle Geminiを使ってLinkedInから企業のストーリー生成
前提条件
- •ターゲットAPIの認証情報が必要な場合あり
- •Google Gemini API Key
使用ノード (19)
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
{
"id": "q1DorytEoEw1QLGj",
"meta": {
"instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
"templateCredsSetupCompleted": true
},
"name": "Generate Company Stories from LinkedIn with Bright Data & Google Gemini",
"tags": [
{
"id": "ddPkw7Hg5dZhQu2w",
"name": "AI",
"createdAt": "2025-04-13T05:38:08.053Z",
"updatedAt": "2025-04-13T05:38:08.053Z"
},
{
"id": "rKOa98eAi3IETrLu",
"name": "HR",
"createdAt": "2025-04-13T04:59:30.580Z",
"updatedAt": "2025-04-13T04:59:30.580Z"
}
],
"nodes": [
{
"id": "1424195e-79ec-48e8-9bb6-fbae072aca81",
"name": "「Test workflow」クリック時",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-1440,
245
],
"parameters": {},
"typeVersion": 1
},
{
"id": "509519c2-efe9-4191-87af-9c5c782350d6",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"notes": "Gemini Experimental Model",
"position": [
696,
540
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-thinking-exp-01-21"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"notesInFlow": true,
"typeVersion": 1
},
{
"id": "3be8be65-38c2-4500-8676-925bdf7844ac",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
816,
542.5
],
"parameters": {
"options": {}
},
"typeVersion": 1
},
{
"id": "65b72f55-6424-487b-a622-879589d43344",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
904,
740
],
"parameters": {
"options": {},
"chunkOverlap": 100
},
"typeVersion": 1
},
{
"id": "4ab31927-5372-4a8f-83b5-355bcd6eaae2",
"name": "If",
"type": "n8n-nodes-base.if",
"position": [
-340,
170
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "6a7e5360-4cb5-4806-892e-5c85037fa71c",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Check Snapshot Status').item.json.status }}",
"rightValue": "ready"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "30382d3b-6ba8-4a96-93ce-9d22fc547793",
"name": "Set Snapshot Id",
"type": "n8n-nodes-base.set",
"position": [
-780,
245
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "2c3369c6-9206-45d7-9349-f577baeaf189",
"name": "snapshot_id",
"type": "string",
"value": "={{ $json.snapshot_id }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "a4867b6f-fa91-4b83-befc-9ce97c10228c",
"name": "Download Snapshot",
"type": "n8n-nodes-base.httpRequest",
"position": [
100,
120
],
"parameters": {
"url": "=https://api.brightdata.com/datasets/v3/snapshot/{{ $json.snapshot_id }}",
"options": {
"timeout": 10000
},
"sendQuery": true,
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"queryParameters": {
"parameters": [
{
"name": "format",
"value": "json"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "kdbqXuxIR8qIxF7y",
"name": "Header Auth account"
}
},
"typeVersion": 4.2
},
{
"id": "16580d94-23fc-45d6-a282-640148b602d3",
"name": "Set LinkedIn URL",
"type": "n8n-nodes-base.set",
"position": [
-1220,
245
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "47f839a1-df2a-4972-9dad-597a8af0bf75",
"name": "url",
"type": "string",
"value": "https://il.linkedin.com/company/bright-data"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "be007904-269a-4823-bdd8-1ba5b4f69f5c",
"name": "Google Gemini Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
408,
340
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "56a08c75-5122-483e-af0e-da1dd3e08eaf",
"name": "Check on the errors",
"type": "n8n-nodes-base.if",
"position": [
-120,
120
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "b267071c-7102-407b-a98d-f613bcb1a106",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.errors.toString() }}",
"rightValue": "0"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "6925a606-1108-4605-9124-c74d3df555ac",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1420,
-100
],
"parameters": {
"width": 400,
"height": 280,
"content": "## Note\n\nDeals with the LinkedIn data extraction using the Bright Data Web Scrapper API.\n\nThe information extraction and summarization are being used to demonstrate the usage of the N8N AI capabilities.\n\n**Please make sure to set the LinkedIn URL and Webhook Notification URL**"
},
"typeVersion": 1
},
{
"id": "a5f977db-14e5-4652-b2d3-0a1b0470be9a",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-940,
-100
],
"parameters": {
"width": 420,
"height": 280,
"content": "## LLM Usages\n\nGoogle Gemini Flash Exp model is being used.\n\nInformation extraction is being used for formatting the LinkedIn response to produce a story.\n\nSummarization Chain is being used for summarization of the content"
},
"typeVersion": 1
},
{
"id": "ae6377e2-6ca0-4218-affd-d3c81c16d996",
"name": "Perform LinkedIn Web Request",
"type": "n8n-nodes-base.httpRequest",
"position": [
-1000,
245
],
"parameters": {
"url": "https://api.brightdata.com/datasets/v3/trigger",
"method": "POST",
"options": {},
"jsonBody": "=[\n {\n \"url\": \"{{ $json.url }}\"\n }\n]",
"sendBody": true,
"sendQuery": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"queryParameters": {
"parameters": [
{
"name": "dataset_id",
"value": "gd_l1vikfnt1wgvvqz95w"
},
{
"name": "include_errors",
"value": "true"
}
]
},
"headerParameters": {
"parameters": [
{}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "kdbqXuxIR8qIxF7y",
"name": "Header Auth account"
}
},
"typeVersion": 4.2
},
{
"id": "9a1e8d92-24a9-481c-b81f-5e37bca46fe2",
"name": "Check Snapshot Status",
"type": "n8n-nodes-base.httpRequest",
"position": [
-560,
245
],
"parameters": {
"url": "=https://api.brightdata.com/datasets/v3/progress/{{ $json.snapshot_id }}",
"options": {},
"sendHeaders": true,
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "kdbqXuxIR8qIxF7y",
"name": "Header Auth account"
}
},
"typeVersion": 4.2
},
{
"id": "543d6087-c1d8-4f98-9b7c-fedbce9b0215",
"name": "LinkedIn Data Extractor",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
320,
120
],
"parameters": {
"text": "=Write a complete story of the provided company information in JSON. Use the following Company info to produce a story or a blog post. Make sure to incorporate all the provided company context.\n\nHere's the Company Info in JSON - {{ $json.input }}",
"options": {
"systemPromptTemplate": "You are an expert data formatter"
},
"attributes": {
"attributes": [
{
"name": "company_story",
"required": true,
"description": "Detailed Company Info"
}
]
}
},
"typeVersion": 1
},
{
"id": "d07c83f0-5adf-4d5a-976a-b344aa8a853e",
"name": "Concise Summary Generator",
"type": "@n8n/n8n-nodes-langchain.chainSummarization",
"position": [
712,
320
],
"parameters": {
"options": {
"summarizationMethodAndPrompts": {
"values": {
"prompt": "=Write a concise summary of the following:\n\n\n{{ $json.output.company_story }}\n\n",
"combineMapPrompt": "=Write a concise summary of the following:\n\n\n\n\n\nCONCISE SUMMARY: {{ $json.output.company_story }}"
}
}
},
"operationMode": "documentLoader"
},
"typeVersion": 2
},
{
"id": "0867753e-c3ab-473e-960a-344573cdde29",
"name": "Webhook Notifier for Data Extractor",
"type": "n8n-nodes-base.httpRequest",
"position": [
834,
-80
],
"parameters": {
"url": "https://webhook.site/ce41e056-c097-48c8-a096-9b876d3abbf7",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "response",
"value": "={{ $json.output }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "d666cbb8-64bf-47b9-802a-d78ed5caa128",
"name": "Webhook Notifier for Summary Generator",
"type": "n8n-nodes-base.httpRequest",
"position": [
1192,
320
],
"parameters": {
"url": "https://webhook.site/ce41e056-c097-48c8-a096-9b876d3abbf7",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "response",
"value": "={{ $json.response.text }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "fbd962be-5003-4039-b17e-fc0f16c2edf7",
"name": "Wait for 30 seconds",
"type": "n8n-nodes-base.wait",
"position": [
-120,
345
],
"webhookId": "f2aafd71-61f2-4aa4-8290-fa3bbe3d46b9",
"parameters": {
"amount": 30
},
"typeVersion": 1.1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "0f4279a9-1593-421e-825e-850cdae1bb97",
"connections": {
"4ab31927-5372-4a8f-83b5-355bcd6eaae2": {
"main": [
[
{
"node": "56a08c75-5122-483e-af0e-da1dd3e08eaf",
"type": "main",
"index": 0
}
],
[
{
"node": "fbd962be-5003-4039-b17e-fc0f16c2edf7",
"type": "main",
"index": 0
}
]
]
},
"30382d3b-6ba8-4a96-93ce-9d22fc547793": {
"main": [
[
{
"node": "9a1e8d92-24a9-481c-b81f-5e37bca46fe2",
"type": "main",
"index": 0
}
]
]
},
"16580d94-23fc-45d6-a282-640148b602d3": {
"main": [
[
{
"node": "ae6377e2-6ca0-4218-affd-d3c81c16d996",
"type": "main",
"index": 0
}
]
]
},
"a4867b6f-fa91-4b83-befc-9ce97c10228c": {
"main": [
[
{
"node": "543d6087-c1d8-4f98-9b7c-fedbce9b0215",
"type": "main",
"index": 0
}
]
]
},
"56a08c75-5122-483e-af0e-da1dd3e08eaf": {
"main": [
[
{
"node": "a4867b6f-fa91-4b83-befc-9ce97c10228c",
"type": "main",
"index": 0
}
]
]
},
"3be8be65-38c2-4500-8676-925bdf7844ac": {
"ai_document": [
[
{
"node": "d07c83f0-5adf-4d5a-976a-b344aa8a853e",
"type": "ai_document",
"index": 0
}
]
]
},
"fbd962be-5003-4039-b17e-fc0f16c2edf7": {
"main": [
[
{
"node": "9a1e8d92-24a9-481c-b81f-5e37bca46fe2",
"type": "main",
"index": 0
}
]
]
},
"9a1e8d92-24a9-481c-b81f-5e37bca46fe2": {
"main": [
[
{
"node": "4ab31927-5372-4a8f-83b5-355bcd6eaae2",
"type": "main",
"index": 0
}
]
]
},
"543d6087-c1d8-4f98-9b7c-fedbce9b0215": {
"main": [
[
{
"node": "d07c83f0-5adf-4d5a-976a-b344aa8a853e",
"type": "main",
"index": 0
},
{
"node": "0867753e-c3ab-473e-960a-344573cdde29",
"type": "main",
"index": 0
}
]
]
},
"509519c2-efe9-4191-87af-9c5c782350d6": {
"ai_languageModel": [
[
{
"node": "d07c83f0-5adf-4d5a-976a-b344aa8a853e",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"d07c83f0-5adf-4d5a-976a-b344aa8a853e": {
"main": [
[
{
"node": "d666cbb8-64bf-47b9-802a-d78ed5caa128",
"type": "main",
"index": 0
}
]
]
},
"be007904-269a-4823-bdd8-1ba5b4f69f5c": {
"ai_languageModel": [
[
{
"node": "543d6087-c1d8-4f98-9b7c-fedbce9b0215",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"ae6377e2-6ca0-4218-affd-d3c81c16d996": {
"main": [
[
{
"node": "30382d3b-6ba8-4a96-93ce-9d22fc547793",
"type": "main",
"index": 0
}
]
]
},
"65b72f55-6424-487b-a622-879589d43344": {
"ai_textSplitter": [
[
{
"node": "3be8be65-38c2-4500-8676-925bdf7844ac",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"1424195e-79ec-48e8-9bb6-fbae072aca81": {
"main": [
[
{
"node": "16580d94-23fc-45d6-a282-640148b602d3",
"type": "main",
"index": 0
}
]
]
}
}
}よくある質問
このワークフローの使い方は？
上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。
このワークフローはどんな場面に適していますか？
上級 - 営業, 人工知能, マーケティング
有料ですか？
このワークフローは完全無料です。ただし、ワークフローで使用するサードパーティサービス（OpenAI APIなど）は別途料金が発生する場合があります。
関連ワークフロー
Amazon製品の価格下落をBright Dataで抽出・要約・分析
Bright DataとGoogle GeminiでAmazonの価格下落情報を抽出・要約・分析
Set
Wait
Merge
+
Set
Wait
Merge
26 ノードRanjan Dailata
人工知能
ビング・データとGemini AIを使ってBing Copilot検索結果を抽出・要約
Gemini AIとBright Dataを使ってBing Copilot検索性別結果を抽出し、要約する
If
Set
Wait
+
If
Set
Wait
19 ノードRanjan Dailata
人工知能
Indeed社データスクレイピングとAirtable、Bright Data、Google Geminiの統合
Airtable、Bright Data、Google Geminiを用いたIndeedデータのスクレイピングと集約
If
Set
Wait
+
If
Set
Wait
19 ノードRanjan Dailata
人事
Bright DataとGoogle Geminiを使ってアマゾンの電子製品ベストセラー情報を抽出
Bright DataとGoogle Geminiを使ってAmazonの電子書籍セールスランキング情報を抽出
Set
Http Request
Manual Trigger
+
Set
Http Request
Manual Trigger
8 ノードRanjan Dailata
営業
Bright Dataを使用したブランドコンテンツの抽出・要約・感情分析
Bright DataとGoogle Geminiを使用してブランドコンテンツを抽出および分析
Set
Function
Http Request
+
Set
Function
Http Request
23 ノードRanjan Dailata
人工知能
Googleトレンドデータ抽出、Bright DataとGoogle Geminiを使用して要約生成
Bright DataとGoogle Geminiを利用したGoogleトレンドデータ抽出と要約生成
Set
Gmail
Function
+
Set
Gmail
Function
16 ノードRanjan Dailata
エンジニアリング
